Experimental design as a tool for parameter optimization of photoelectrocatalytic degradation of a textile dye

• Autor(a) principal: Bessegato, Guilherme G. [UNESP]
• Data de Publicação: 2019
• Outros Autores: De Almeida, Lucio C. [UNESP], Ferreira, Sérgio L.C., Zanoni, Maria Valnice Boldrin [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.jece.2019.103264; http://hdl.handle.net/11449/190497
• topic: Azo dye; Counter electrode material; Doped TiO2; Photoelectrocatalysis; Response surface methodology

Although several factors are found to influence the efficiency of photoelectrocatalytic oxidation, univariate optimization may not provide some relevant information, such as the existence of interaction between the factors. This article describes the optimization of photoelectrocatalytic parameters by response surface methodology (RSM) using a two-level full factorial composite design with center point. The factors investigated included pH, bias potential and counter electrode material (C.E.) employed in the photoelectrocatalytic degradation of 50 mg L-1 Acid Red 151 (AR151) azo dye (taken as a model textile dye) in 0.01 mol L-1 Na2SO4 electrolyte, using boron-doped TiO2 nanotube (B-TNT) photoanode under UV/Vis Hg lamp irradiation. The responses evaluated were total organic carbon removal and decolorization. The results showed that all the factors exerted a significant effect, among which the pH was the variable with the greatest impact on the PEC treatment. Although less significant, interactions between the variables, such as pH and the counter electrode, were observed for both responses. The best conditions for the photoelectrocatalytic degradation of AR151 dye were pH 2.0 and potential of 2.0 V using graphite as counter electrode. Photoelectrocatalytic treatment of 50 mg L-1 of AR151 dye reached total decolorization in 30 min and almost total mineralization after 90 min. The findings show that the use of RSM to optimize degradation conditions helps to save time and chemicals, in addition to contributing toward a better understanding of the factors that affect photoelectrocatalytic performance.